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Location Domestic International
Lismore
National Marine Science Centre Coffs Harbour
Online

Unit Summary

Unit type

UG Coursework Unit

Credit points

12

Unit aim

Data management and analysis are essential tools for scientists. This unit provides students with basic skills in data management, illustration, analysis, and interpretation that will be foundational for careers in science and science-related disciplines. The unit will examine different types of data and how to compare and present them in a scientific manner. It covers introductory-level analyses such as t-tests, ANOVA, correlation and regression, and Chi-square tests. Emphasis is placed on matching data with appropriate statistical tests to provide students with knowledge on how to answer simple scientific hypotheses. The unit also gives an overview of experimental designs and sampling strategies for data collection that can be applied across disciplines.

Unit content

1. Scientific measurements and data

2. Data management

3. Measures for summarising and describing data

4. Statistically comparing data between two groups

5. Statistically comparing more than two groups of data

6. Analysing relationships: correlation and regression

7. Analysing categorical data

8. Experimental and survey designs

Learning outcomes

Unit Learning Outcomes express learning achievement in terms of what a student should know, understand and be able to do on completion of a unit. These outcomes are aligned with the graduate attributes. The unit learning outcomes and graduate attributes are also the basis of evaluating prior learning.

On completion of this unit, students should be able to:
1 understand and calculate descriptive statistics for a variety of scientific data types
2 apply data management skills to organise, analyse and display data
3 identify appropriate statistical analyses to test hypotheses and perform basic statistical analyses
4 present and interpret results of statistical analyses in a professional manner.

On completion of this unit, students should be able to:

  1. understand and calculate descriptive statistics for a variety of scientific data types
  2. apply data management skills to organise, analyse and display data
  3. identify appropriate statistical analyses to test hypotheses and perform basic statistical analyses
  4. present and interpret results of statistical analyses in a professional manner.

Prescribed texts

  • No prescribed texts.
Prescribed texts may change in future teaching periods.